Spectral fatigue analysis approach is highly recommended for fixed offshore platform design and reassessment by API. This method is a computationally efficient method, being able to handle the random nature of environmental ocean wave conditions during calculating wave loads on the offshore platforms and subsequent structural responses. However, its fundamental theory is based on the assumption of linearity of both structural system and wave loading mechanism. Although this method is critically appropriate to be applied in offshore platform design and fatigue assessment for deep water scenarios where wave and force nonlinearities are not very severe, it has still been widely utilized for the design and assessment of shallow water platforms in offshore industry without carefully considering possible errors caused by strong nonlinear factors between ocean waves and forces. The source giving rise to the errors is because of the difficulties in choosing suitably correct wave heights for a series of wave periods required for producing transfer functions between sea state spectra and structural response spectra. Therefore, the studies to justify the possible errors of the spectral fatigue analysis method for shallow water platforms have been provoked. This paper presents the results of the studies of investigating the errors from currently existing spectral fatigue analysis method. A new technical approach that can reduce the errors in the spectral fatigue analysis of shallow water platforms is introduced. The proposed technical approach is mainly focused on producing realistic transfer functions between sea state spectra and structural response spectra, which can reasonably reflect the individually local sea state data by using wave height-period joint probability density function. Hence the fatigue damage and life at the tubular joints of offshore platforms can be more precisely predicted. The spectral fatigue analysis of a practical shallow water jacket platform in the recent platform design project has been performed using the proposed approach and the results are discussed.
The spectral analysis approach is a very elegant and computationally efficient method of analyzing the fatigue life of offshore jacket platforms. The primary limitation of the approach is that it assumes linearity of both the structural system and the wave-loading mechanism. The approach is now widely used for the analysis of deepwater, dynamically responsive platforms where nonlinearities are usually not serious. There are also advantages associated with using the approach for shallow water platforms although nonlinearities then become significant, particularly the wave-loading mechanism. Various methods have been proposed to enable the spectral method to be used for some nonlinear situations, including a new approach which uses the Longuet-Higgins wave height-period joint probability density function in order to obtain a better linearization technique. This linearization process is associated with the particular wave heights chosen for producing the transfer functions. The new approach provides a better method for choosing the appropriate height of each so-called base wave case. In order to verify the new approach, a time series analysis, including wave-loading nonlinearities, has been adopted to obtain a reference fatigue life. The sea surface elevation spectrum has been decomposed into a set of equivalent harmonic components. The water particle velocities and accelerations were then individually evaluated and the appropriate (Morison’s) wave loading was computed for each time step in the sea surface time history. The structural stress response time history was then calculated, from which a fatigue life estimate was obtained. This paper presents the results obtained using this new approach, as well as comparative results obtained using the deterministic, spectral, and time domain approaches applied with a representative sea state. The results show that the deterministic-spectral method has a considerable amount of potential, especially for new design work where weight savings and/or increased confidence levels may be achieved.
For reducing the computational complexity of direction-finding algorithm in sparse multipleinput multiple-output (MIMO) radar, a low-complexity partial spatial smoothing (PSS) algorithm is presented to estimate the directions of multiple targets. Firstly, by dealing with a partly continuous sampling covariance vector in PSS technology, an incomplete signal subspace can be obtained. Then, a special matrix can be obtained by using this incomplete signal subspace. Meanwhile the incomplete signal subspace can also be repaired by the special matrix. At last, the multiple signal classification (MUSIC) algorithm is used to obtain direction estimations. In the process of obtaining signal subspace, no eigenvalue decomposition (EVD) needs to be performed. Compared with the traditional spatial smoothing (SS) technology, the proposed algorithm has lower computational complexity and higher estimation accuracy. Many simulation results are provided to support the proposed scheme.
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